Titanium dioxide replacement with inorganic alternatives for color‐masking of ferrous fumarate in double fortified salt
Bibliographic record
Abstract
Abstract Background Titanium dioxide (TiO2) has been widely used in food products, including gums, candies and in fortified salt as a white coloring agent of iron premixes. TiO2 (E171) was banned by the European Food Safety Authority in 2021, with potential carcinogenicity concerns. This study assesses the feasibility of using inorganic alternatives to replace TiO2 in ferrous fumarate‐based iron premixes for salt fortification for treatment of iron and iodine deficiencies. Results Varying levels of alternatives were utilized: calcium carbonate, magnesium carbonate, zinc oxide, calcium sulfate, and commercial formulations Opadry®, and Nutrafinish®. Adhesives included HPMC and gum Arabic with soy stearin as an overcoat moisture barrier. Preliminary results for MgCO3 premixes had poor adhesion, leading to exposed iron, which will be addressed in further studies. ZnO, Opadry, CaCO3 and CaSO4 premixes resembled TiO2 premixes in terms of coverage and color, especially CaSO4, attributed to calcium sulfate's small particle size resulting in high surface area for coverage. Premixes stored in iodized salt at 25, 35, 45°C and elevated humidity, for 9‐month stability studies retained over 70% iodine, confirming successful encapsulation. Conclusions CaSO4, CaCO3 and ZnO premixes were successful in terms of appearance and stability of fortificants over 9‐month storage. The levels of calcium in fortified salt were lower than that which would impede iron absorption. Therefore, these calcium and zinc alternatives would be suitable alternatives to titanium dioxide premix for use in fortified salts. Premixes will be scaled‐up for cost‐effective salt fortification to address micronutrient deficiencies in low middle income countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".